sutro-sh/jev-align

Build calibrated AI Functions from human feedback using Jev and GEPA.

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jev-align is an experimental CLI from Sutro for building AI Functions with TypeSafe's Jev. It finds uncertain examples, asks you to label them, and uses GEPA to improve the function. Use it in your application and keep learning from production examples. https://github.com/user-attachments/assets/81650587-e3f1-4655-8213-ed5f6e120e9a Requires Python 3.11 or newer. Start the CLI with either jeva or jev-align. Use pip install jev-align if you do not use uv. The guided setup discovers local CSV, Parquet, and JSONL files and includes three ready-to-run examples. Each round: Every label comes from you. A higher training score never accepts a proposal automatically. The guided Advanced menu configures: By default, jev-align uses the first 1,000 rows—or the entire dataset when it is smaller—and lets you concatenate all fields or select specific columns. Everything can also be configured with flags: Use repeated --class "NAME=DESCRIPTION" options for multiclass or multilabel tasks, and repeated --score-level options for scoring tasks. Run…

sutro-sh/jev-align on GitHub A short preview, not the full document.

Read the full README ↗ · Preview checked 2026-09-20T08:32:42.305Z

Inside the original README — Document outline
  1. jev-align
  2. Demo
  3. Quick start
  4. How it works
  5. Task types
  6. Configuration
  7. Jev providers
  8. Reflection models
  9. Controls
  10. Saved AI Functions
  11. Keep learning from production
  12. Using a coding agent

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Documentation belongs to its respective authors. Reported project/model license: Apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.

What this repository does

Build calibrated AI Functions from human feedback using Jev and GEPA.

Repository facts

Owner
sutro-sh
Primary language
Python
Stars
249
Forks
19
Open issues + pull requests
1
License
Apache-2.0
Archived
No
Default branch
main
Created
2026-09-19T02:12:23.000Z
Last push
2026-09-20T20:50:08.000Z

Topics and intended use

Owner-supplied topics: active-learning, classification, cli, gepa, human-in-the-loop, jev, prompt-optimization, typesafe-ai

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Source: GitHub. Metadata observed 2026-09-21T06:41:42.808Z. Daily imports are snapshots, not real-time monitoring.

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